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Abstract Background Various treatments have been employed in managing type B aortic dissection (TBAD), encompassing open surgical repair (OSR), thoracic endovascular aortic repair (TEVAR), and optimal medical therapy (OMT). Nonetheless, the determination of the most efficacious treatment protocol remains a subject of debate. We aim to compare the treatments in patients with acute and subacute TBAD using a meta-analytic approach. Methods A systematic search was conducted across databases including PubMed, EmBase, and the Cochrane Library for relevant studies published from their inception up to September 2024. Studies comparing OSR, TEVAR, and OMT for TBAD through controlled or direct comparative designs were incorporated. Pairwise comparison meta-analyses were performed employing odds ratios (OR) alongside 95% confidence intervals (CIs) to quantify intervention effects by using the random-effects model. Results Thirty-one studies involving 34,681 patients with TBAD were included in the final meta-analysis. We noted OSR were associated with an increased risk of in-hospital mortality (OR: 2.41; 95%CI: 1.67–3.49; P

Abstract Polyetheretherketone (PEEK) is widely used in orthopedic and dental implants due to its excellent mechanical properties, chemical stability, and biocompatibility. However, its inherently bioinert nature makes it present weak osteogenic activity, which greatly restricts its clinical adoption. Herein, strontium (Sr) is incorporated onto the surface of PEEK using mussel-inspired polydopamine coating to improve its osteogenic activity. X-ray photoelectron spectroscopy and ion release assay results confirm that different concentrations of Sr are incorporated onto the PEEK substrate surfaces. The strontium-modified PEEK samples show a stable Sr ion release in 35 days of detection. Better results of MC3T3-E1 pre-osteoblasts adhesion, spreading, and proliferation can be observed in strontium-modified PEEK groups, which demonstrates strontium-modified PEEK samples with the improved MC3T3-E1 pre-osteoblasts compatibility. The boosted osteogenic activity of strontium-modified PEEK samples has been demonstrated by the better performed of ALP activity, extracellular matrix mineralization, collagen secretion, and the remarkable up-regulation of ALP, OCN, OPN, Runx2, Col-I, BSP, and OSX of the MC3T3-E1 pre-osteoblasts. Additionally, the strontium-modified PEEK samples exhibit a dose-dependent enhancement of osteoblasts compatibility and osteogenic activity, and the PEEK-Sr10 group shows the best. These findings indicate that strontium-decorated PEEK implants show promising application in orthopedic and dental implants.

Abstract To adapt to the dynamic, diverse, and personalised needs of customers, manufacturing enterprises face the challenge of continuously adjusting their resource structure. This has led manufacturers to shift towards a smart cloud manufacturing mode in order to build highly flexible production logistics (PL) systems. In these systems, the optimal configuring of PL resources is fundamental for daily logistics planning and vehicle scheduling control, providing necessary resources for the entire PL segment. However, traditional resource configuration methods face limitations, such as incomplete information acquisition, slow response in resource configuration, and suboptimal configuration results, leading to high subsequent operational costs and inefficient logistics transportation. These issues limit the performance of the PL system. To address these challenges, the authors propose a digital twin‐based optimisation model and method for smart cloud PL resources. The approach begins with constructing an optimisation model for the PL system considering the quality of service for a cloud resource is constructed, aiming to minimise the number of logistics vehicles and the total cost of the PL system. Additionally, a DT‐based decision framework for optimising smart cloud PL resources is proposed. Alongside a DT‐based dynamic configuration strategy for smart cloud PL resources is designed. By developing a multi‐teacher grouping teaching strategy and a cross‐learning strategy, the teaching and learning strategies of the standard teaching‐learning‐based optimisation algorithm are improved. Finally, numerical simulation experiments were conducted on the logistics transportation process of a cooperating enterprise, verifying the feasibility and effectiveness of the proposed algorithms and strategies. The findings of this study provide valuable references for the management of PL resources and algorithm design in advanced manufacturing modes.

Correctly identifying influential nodes in a complex network and implementing targeted protection measures can significantly enhance the overall security of the network. Currently, indicators such as degree centrality, closeness centrality, betweenness centrality, H-index, and K-shell are commonly used to measure node influence. Although these indicators can identify critical nodes to some extent, they often consider node attributes from a narrow perspective and have certain limitations. Therefore, evaluating the importance of nodes using most existing indicators remains incomplete. In this paper, we propose the multi-attribute CRITIC-TOPSIS network decision indicator, or MCTNDI, which integrates closeness centrality, betweenness centrality, H-index, and network constraint coefficients to identify critical nodes in a network. This indicator combines information from multiple perspectives, including local neighborhood importance, network topological location, path centrality, and node mutual information, thereby solving the issue of the one-sided perspective of single indicators and providing a more comprehensive measure of node importance. Additionally, MCTNDI is validated through the analysis of several real-world networks, including the Contiguous USA network, Dolphins network, USAir97 network, and Tech-routers-rf network. The validation is conducted from four aspects: the results of simulated network attacks, the distribution of node importance, the monotonicity of rankings, and the similarity of indicators, illustrating MCTNDI’s effectiveness in real networks.

IntroductionAcupuncture is a Traditional Chinese Medicine (TCM) method that achieves therapeutic effects through the interaction of neurotransmitters and neural regulation. It is generally carried out manually, making the related process expert-biased. Meanwhile, the neural stimulation effect of acupuncture is difficult to track objectively. In recent years, virtual reality (VR) in medicine has been on the fast lane to widespread use, especially in therapeutic stimulation. However, the use of related technologies in acupuncture has not been reported.MethodsIn this work, a novel acupuncture stimulation technique using VR is proposed. To track the stimulation effect, the electroencephalogram (EEG) is used as the marker to validate brain activities under acupuncture.Results and discussionAfter statistically analyzing the data of 24 subjects during acupuncture at the “Zusanli (ST36)” acupoint, it has been determined that Virtual Acupuncture (VA) has at least a 63.54% probability of inducing similar EEG activities as in Manual Acupuncture (MA). This work may provide a new solution for researchers and clinical practitioners using Brain-Computer Interface (BCI) in acupuncture.

BackgroundPrimary cardiac lymphoma is an extremely rare malignant lymphoma, with clinical manifestations related to its location. We reported the diagnosis and treatment of primary cardiac lymphoma in a patient presented with atrioventricular block.Case presentationA 64 year-old man was admitted to our hospital because of symptoms of a tired heart and shortness of breath. The initial electrocardiogram revealed a third-degree atrioventricular block. Computed tomography scan showed an irregularly shaped right heart, irregular clusters, and relatively weakly enhanced areas in the right auricle, atrium, and ventricle. The local boundary between the lesion, pericardium, and left atrium was unclear, and the ventricular septum was irregular and thickened. Multiple irregular gray neoplasms with less smooth surfaces were observed, with a maximum diameter of approximately 7 cm. Pathological findings confirmed a non-germinal center B cell subtype of diffuse large B-cell lymphoma. After surgical resection of the tumor and implantation of a permanent pacemaker, the symptoms of the patient were significantly improved, allowing subsequent chemotherapy.ConclusionSurgical resection and placement of a permanent pacemaker were effective treatments for a patient with primary cardiac lymphoma presented with atrioventricular block.

This study aims to achieve intelligent fusion and unified modeling to meet the requirements of multi-source and heterogeneous big data granulation for knowledge discovery in the field of water resources. The paper focuses on decision-making data granulation and knowledge discovery driven by big data in the field of water resources. It utilizes a combination of domain numerical simulation and model verification to systematically investigate decision-oriented big data multi-granularity granulation and knowledge discovery. The study reveals the mechanism and law of the transformation of management and decision-making paradigm driven by big data. This study results include the development of a granulation mechanism and a semantic fusion method for multi-source and heterogeneous big data, a multi-scale granular structure for big data, multi-granularity feature discovery and granulation method, and a multi-granularity uncertainty reasoning and knowledge discovery method. The proposed dynamic big data fusion and knowledge discovery approach effectively supports big data granulation and knowledge discovery in water resource decision-making. The study found that the proposed dynamic big data multi-granularity fusion method outperforms existing dynamic big data correlation analysis methods and greatly reduces data processing time.

Abstract Background The majority of postoperative complications of tonsillectomy are bleeding. However, massive cerebral infarction following haemostasis is a very rare and serious complication and has rarely been reported clinically. Case presentation We performed a left tonsillectomy on a patient with chronic tonsillitis. After that, active bleeding was found under the tonsillar fossa, so an exploratory hypopharyngeal haemostasis was performed. However, the bleeding worsened intraoperatively, so the patient was converted to a cervical angiographic embolization. The interventional procedure was completed successfully without an ectopic embolic event. After the procedure, the patient was transferred to the intensive care unit (ICU) and was diagnosed with acute massive cerebral infarction in the left cerebral hemisphere after awakening symptoms combined with cranial computed tomography angiography (CTA) results. Symptomatic treatment such as sedation and analgesia, dehydration to lower intracranial pressure, and maintenance of respiratory and circulatory stability was then administered. After treatment, the patient’s condition stabilized and he was transferred to the rehabilitation physiotherapy unit for rehabilitation. Conclusion Post-tonsillectomy haemorrhage can be augmented with a carotid arteriogram to clarify whether the tonsillar fossa is at a safe distance from the posterior internal carotid artery. Furthermore, interventional haemostasis can also be performed as early as possible to reduce the incidence of complications in cases of persistent post-tonsillectomy bleeding.

Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet’s increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer meet the needs of network security analysis. Therefore, we conduct research based on a multi-layer network model for network security situational awareness, which is characterized by the three-layer network structure of a physical device network, a business application network, and a user role network. Its network characteristics require new assessment methods, so we propose a multi-layer network link importance assessment metric: the multi-layer-dependent link entropy (MDLE). On the one hand, the MDLE comprehensively evaluates the connectivity importance of links by fitting the link-local betweenness centrality and mapping entropy. On the other hand, it relies on the link-dependent mechanism to better aggregate the link importance contributions in each network layer. The experimental results show that the MDLE has better ordering monotonicity during critical link discovery and a higher destruction efficacy in destruction simulations compared to classical link importance metrics, thus better adapting to the critical link discovery requirements of a multi-layer network topology.

Ball-shell rotors with non-standard shapes, non-uniform conductive coatings, and eccentric masses machined by conventional processes constrain the improvement of levitation and torque accuracy of magnetically levitated momentum balls. This paper focuses on the machining method of multilayer ball-shell rotors to develop a ball-shell rotor with a standard shape and uniform conductive coating, which can improve the levitation and torque accuracy of magnetically levitated momentum balls. In this paper, a machining method for multi-coated ball-shell rotors is proposed. The machining process combining hemispherical surface and workpiece is adopted, and the whole sphere is assembled by threading, which effectively reduces the machining error. The influence of the cutting depth and feed rate of the tool on the cutting force of the ball shell was analyzed through the cutting force model. The effect of cutting force on the deformation of the ball shell was analyzed by the finite element method. The superiority of the machining method was verified by measuring the dimensions of the ball shell with a coordinate measuring machine. Compared with the traditional machining process and assembly method, the proposed ball-shell rotor machining method effectively improves the dimensional accuracy, reduces the center of mass to center of mass deviation, and ensures the levitation accuracy and output torque accuracy of the magnetically levitated momentum ball. Measurement results show that the diameter values of the pure iron ball shell are between 98.694 and 98.707 mm with a machining error of ±0.007 mm, and the diameter values of the spray-painted ball shell are between 99.490 and 99.510 mm with a machining error of ±0.01 mm. The machining static equilibrium of the pure iron ball shell and the spray-painted ball shell is good by the static equilibrium test method.

Improving the effectiveness of target link importance assessment strategy has become an important research direction within the field of complex networks today. The reasearch shows that the link importance assessment strategy based on betweenness centrality is the current optimal solution, but its high computational complexity makes it difficult to meet the application requirements of large-scale networks. The k-core decomposition method, as a theoretical tool that can effectively analyze and characterize the topological properties of complex networks and systems, has been introduced to facilitate the generation of link importance assessment strategy and, based on this, a link importance assessment indicator link shell has been developed. The strategy achieves better results in numerical simulations. In this study, we incorporated topological overlap theory to further optimize the attack effect and propose a new link importance assessment indicator link topological shell called t-shell. Simulations using real world networks and scale-free networks show that t-shell based target link importance assessment strategies perform better than shell based strategies without increasing the computational complexity; this can provide new ideas for the study of large-scale network destruction strategies.

Background: Combination therapy has become an attractive option in pulmonary arterial hypertension (PAH) treatment. The aim of this study was to investigate whether additional use of prostacyclin analogs could exert any additional benefits over background targeted therapies in PAH patients.Methods: Searches were performed on PubMed, Embase, and ClinicalTrials.gov from inception to 1 October 2021. Randomized controlled trials were included if patients had been treated with prostacyclin analog-containing combination therapy and compared with the use of other PAH-specific background therapies. The bias risk and statistical analysis of the enrolled studies were performed with RevMan 5.1. Sensitivity analysis and funnel plot were used to evaluate the stability and publication bias, respectively. PROSPERO registered number CRD42021284196.Results: Ten trials involving 1828 patients were included. Prostacyclin analog treatment was associated with greater improvement in clinical worsening (risk ratio [RR], 0.70; 95% confidence interval [CI], 0.57–0.86), 6-min walk distance (mean difference [MD], 37.17 m; 95% CI, 3.01–71.33 m), NYHA/WHO functional class (RR, 1.58; 95% CI, 1.21–2.05), mean pulmonary artery pressure (MD, −9.23 mmHg; 95% CI, −17.44 to −1.03 mmHg), and cardiac index (MD, 0.41 L/min/m2; 95% CI, 0.26–0.55 L/min/m2) than the control group. No significant differences in pulmonary vascular resistance (MD, −137.22 dyn·s/cm5; 95% CI, −272.61 to −1.84 dyn·s/cm5) and all-cause mortality (RR, 0.96; 95% CI, 0.57–1.61) were found between the prostacyclin analog group and control group. Of note, more adverse events (RR, 1.07; 95% CI, 1.02–1.13) occurred in the prostacyclin analog group but no significant increase in serious adverse events (RR, 1.25; 95% CI, 0.75–2.11).Conclusion: Additional prostacyclin analog treatment exerted benefits on clinical worsening, exercise capacity, functional class, mean pulmonary artery pressure, and cardiac index in PAH patients, but it was associated with overall risk of adverse events.Clinical Trial Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021284196, identifier CRD42021284196.

Glutathione S-transferases (GSTs) constitute a large family of enzymes with a wide range of cellular functions. Recently, plant GSTs have gained a great deal of attention due to their involvement in the detoxification of electrophilic xenobiotics and peroxides under adverse environmental conditions, such as salt, cold, UV-B and drought stress. A previous study reported that a GST gene (CsGSTU8) in tea plant was distinctly induced in response to drought, suggesting this gene plays a critical role in the drought stress response. In this study, by using quantitative real-time PCR (qRT-PCR) and β-glucuronidase (GUS) reporter lines, we further demonstrated that CsGSTU8 was upregulated in response to drought stress and exogenous abscisic acid (ABA) treatments. Overexpression of CsGSTU8 in Arabidopsis resulted in enhanced drought tolerance as indicated by the improved scavenging of excess amounts of reactive oxygen species (ROS) under drought conditions. Furthermore, we found that CsWRKY48 acts as a transcriptional activator and that its expression is induced in response to drought stress and ABA treatment. Electrophoretic mobility shift assays (EMSAs), dual-luciferase (LUC) assays and transient expression assays in tea plant leaves revealed that CsWRKY48 directly binds to the W-box elements in the promoter of CsGSTU8 and activates its expression. Taken together, our results provide additional knowledge of drought stress responses in tea plant.

Abstract Background Progress of the aortic disease after the stent graft treatment of aortic dissection implicates the potential risks of stent graft-induced new entry (SINE). Although rarely reported, it should be vigilant in patients who might incur serious complication in early period after the thoracic endovascular aortic repair (TEVAR). Thus, the development of aortic disease-specific stent grafts would assist in achieving positive patient outcomes when suffering SINE. However, it is an extremely rare for SINE between two non-overlapping stent-grafts. Case presentation We here reported a 59-year-old male patient with sudden onset of chest pain for 4 h. Multi-detector computed tomography (MDCT) revealed a huge SINE formed between two non-overlapping stent-grafts. The re-TEVAR surgery was performed and the patient experienced a good recovery. Conclusion The SINE between two non-overlapping stent-grafts treated by re-TEVAR operation was alternative and feasible. The short-term and medium-term follow-up results were satisfactory.

The rapid development of urban industrialization has had many negative effects on the quality of water sources around cities. Long-term prediction of water quality can be of great help to the conservation of water environment. This case tries to use several popular deep learning models, such as RNN, LSTM, MLP, and Transformer-based models to predict the long-term integrated water quality index in the Chaohu Lake area. The dataset is derived from daily monitoring data from four monitoring sites within Chaohu Lake from 2019 to 2022, and the long-term prediction performance of the model is evaluated using MAE and MSE as evaluation metrics. The experimental results showed that all models selected in this case achieved good results within the study area, but Informer performed more prominently (MSE = 0.2455, MAE = 0.2449) as the length of the prediction series increased. Our results demonstrate the effectiveness of popular deep learning models in the field of WQI prediction, especially the significant advantage of transformer-based models represented by Informer in long-term water quality prediction, which will further provide an effective modern tool for water quality monitoring and management.

The human–machine interaction of existing agricultural measurement and control platforms lacks user-friendliness and requires manual operation by trained professionals. The recent development of natural language processing technology may bring some interesting changes. We propose a pipeline for building a natural language human–machine interaction interface to provide a better interaction for agricultural measurement and control platforms. Our construction process uses a new method of collecting training data based on the dynamic tuple language framework to synthesize natural language commands entered by the user into structured AOM statements (Action-Object-Member). To construct a mapping of the human–machine interface from natural language commands to AOM invocations, we propose an end-to-end framework that uses a special mask mechanism to improve the BERT-based Seq2Seq model to capture global sequence relations. Experimental results of data collection methods and NL2AOM demonstrate that our pipeline has good performance and a reasonable response time. Finally, we developed desktop and mobile platform applications based on the proposed model and used them in real agricultural scenarios.

Neonicotinoids are important insecticides for controlling aphids in agriculture. Growing research suggested that neonicotinoid insecticides are a key factor causing the decline of global pollinator insects, such as bees. Flupyrimin (FLP) is a novel nicotinic insecticide with unique biological properties and no cross-resistance, and is safe for pollinators. Using FLP as the lead compound, a series of novel compounds were designed and synthesized by replacing the amide fragment with a sulfonamideone. Their structures were confirmed by 1H NMR, 13C NMR and HRMS spectra. Bioassay results showed that compound 2j had good insecticidal activity against Aphis glycines with an LC50 value of 20.93 mg/L. Meanwhile, compound 2j showed significantly lower acute oral and contact toxicity to Apis mellifera. In addition, compound 2j interacted well with the protein in insect acetylcholine binding protein (AChBP). The molecular docking on honeybee nicotinic acetylcholine receptor (nAChR) indicated that the sulfonamide group of compound 2j did not form a hydrogen bond with Arg173 of the β subunit, which conforms to the reported low bee-toxicity conformation. In general, target compound 2j can be regarded as a bee-friendly insecticide candidate.

The Internet creates multidimensional and complex relationships in terms of the composition, application and mapping of social users. Most of the previous related research has focused on the single-layer topology of physical device networks but ignored the study of service access relationships and the social structure of users on the Internet. Here, we propose a composite framework to understand how the interaction between the physical devices network, business application network, and user role network affects the robustness of the entire Internet. In this paper, a multilayer network consisting of a physical device layer, business application layer and user role layer is constructed by collecting experimental network data. We characterize the disturbance process of the entire multilayer network when a physical entity device fails by designing nodal disturbance to investigate the interactions that exist between the different network layers. Meanwhile, we analyze the characteristics of the Internet-oriented multilayer network structure and propose a heuristic multilayer network topology generation algorithm based on the initial routing topology and networking pattern, which simulates the evolution process of multilayer network topology. To further analyze the robustness of this multilayer network model, we combined a total of six target node ranking indicators including random strategy, degree centrality, betweenness centrality, closeness centrality, clustering coefficient and network constraint coefficient, performed node deletion simulations in the experimental network, and analyzed the impact of component types and interactions on the robustness of the overall multilayer network based on the maximum component change in the network. These results provide new insights into the operational processes of the Internet from a multi-domain data fusion perspective, reflecting that the coupling relationships that exist between the different interaction layers are closely linked to the robustness of multilayer networks.

In large-scale network topology discovery, due to the complex network structure and dynamic change characteristics, it is always the focus of network topology measurement to obtain as many network paths as possible in a short time. In this paper, we propose a large-scale network path probing approach in order to solve the problems of low probing efficiency and high probing redundancy commonly found in current research. By improving the packet delivery order and the update strategy of time-to-live field values, we redesigned and implemented an efficient large-scale network path probing tool. The experimental results show that the method-derived tool can complete path probing for a sample of 12 million/24 network address segments worldwide within 1 hour, which greatly improves the efficiency of network path probing. Meanwhile, compared to existing methods, the proposed method can reduce the number of packets sent by about 10% with the same number of network addresses found, which effectively reduces probing redundancy and alleviates the network load.

Most of the existing electrical-resistivity-based ahead prospecting methods in tunnel use only the tunnel cavity and tunnel face space to locate the water-bearing structures in front of the tunnel. However, due to the limitation of the narrow available space for arranging electrodes in tunnel, this kind of method is difficult to achieve more accurate image for water-bearing structures. The cross-hole electrical resistivity tomography (CHERT) and borehole-to-surface electrical resistivity tomography (BSERT) methods using borehole space have been proved effective means to achieve better images of deep anomalies on the surface. In this paper, the tunnel-face and borehole ERI (TBERI) method in tunnels was studied. To less affect the construction progress, the pole-pole configuration using a single borehole was studied in this paper. Moreover, the configuration is optimized based on the block weighted CR optimization strategy. After considering the data combination, an effective measurement configuration suitable for TBERI detection was formed. To accelerate calculation, some redundant data are removed from the obtained data after proposed block weighted optimization is conducted. By adopting the proposed configuration, the abnormal objects in the target area in the inversion are more accurate. The effectiveness of proposed configuration is verified by numerical simulation.

Tea plant (Camellia sinensis), an important economic crop, is seriously affected by various abiotic stresses, including salt stress, which severely diminishes its widespread planting. However, little is known about the roles of long non-coding RNAs (lncRNAs) in transcriptional regulation under salt stress. In this study, high-throughput sequencing of tea shoots under salt-stress and control conditions was performed. Through sequencing analysis, 16,452 unique lncRNAs were identified, including 172 differentially expressed lncRNAs (DE-lncRNAs). The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of their cis- and trans-target genes showed that these DE-lncRNAs play important roles in many pathways such as the galactinol synthase (GOLS), calcium signaling pathway, and interact with transcription factors (TFs) under salt stress. The data from the gene-specific antisense oligodeoxynucleotide-mediated reduction in the lncRNA MSTRG.139242.1 and its predicted interacting gene, TEA027212.1 (Ca2+-ATPase 13), in tea leaves revealed that MSTRG.139242.1 may function in the response of tea plants to high salinity. In addition, 12 lncRNAs were predicted to be target mimics of 17 known mature miRNAs, such as miR156, that are related to the salt-stress response in C. sinensis. Our results provide new insights into lncRNAs as ubiquitous regulators in response to salt stress in tea plants.

Abstract Background Traumatic aortic arch rupture with pseudoaneurysm is a rare high fatal injury. Thoracic endovascular aortic repair(TEVAR) is widely used in the treatment of aortic diseases. However a unified traumatic aortic injury risk stratification tool still lacks. The patients’ disease assessment and operation method still rely on the doctors’ subjective anticipation of disease and surgical results. Case presentation A 31-year-old male presented with chest pain and hoarseness of recent onset. Imageological examination showed aortic rupture with mediastinal pseudoaneurysm in Zone 1. Debranching + TEVAR hybrid operation was considered: Using artificial blood vessels rebuild the arch branches, the covered stent was placed in aortic arch for endovascular repair via femoral artery. The follow-up was good in postoperative 7d, 1 year and > 2 years. Conclusion The traumatic aortic arch rupture with pseudoaneurysm treated by Debranching+TEVAR hybrid operation is feasible. The short-term and medium-term follow-up results are satisfactory. For traumatic aortic arch injury, hybrid operation is recommended to reduce the risk of cardiopulmonary bypass and deep hypothermia circulatory arrest under no open operation conditions or emergency situation.

Correctly measuring the importance of nodes in a complex network is critical for studying the robustness of the network, and designing a network security policy based on these highly important nodes can effectively improve security aspects of the network, such as the security of important data nodes on the Internet or the hardening of critical traffic hubs. Currently included are degree centrality, closeness centrality, clustering coefficient, and H-index. Although these indicators can identify important nodes to some extent, they are influenced by a single evaluation perspective and have limitations, so most of the existing evaluation methods cannot fully reflect the node importance information. In this paper, we propose a multi-attribute critic network decision indicator (MCNDI) based on the CRITIC method, considering the H-index, closeness centrality, k-shell indicator, and network constraint coefficient. This method integrates the information of network attributes from multiple perspectives and provides a more comprehensive measure of node importance. An experimental analysis of the Chesapeake Bay network and the contiguous USA network shows that MCNDI has better ranking monotonicity, more stable metric results, and is highly adaptable to network topology. Additionally, deliberate attack simulations on real networks showed that the method exhibits high convergence speed in attacks on USAir97 networks and technology routes networks.

With the fast development of urban rail transportation, shield construction has been widely used in tunnel construction in China. It is very important to detect the random distribution of boulders, which may cause geological problems. Cross-hole electrical resistivity tomography (ERT) has the advantage of precise detection, but it has not been systematically studied in solitary rock detection. Therefore, we set up several numerical models and proposed weighted inversion, to improve the capacity for detecting boulders. Subsequently, the method was applied to the Xiamen Metro Line 1, where it was highly likely to encounter boulders. All the test boreholes revealed the presence of boulders, and their location and size were consistent with the geophysics results. This study demonstrated the suitability of weighted inversion based on a multi-configuration combination of cross-hole ERT for the detection of boulders. This case study provides new engineering perspectives on how to detect boulders.

Abstract Objective We modified the conventional aortic arch replacement procedure to avoid circulation arrest and a prolonged extracorporeal circulation time, especially in cases of acute aortic dissection. We herein present our experience with a modified branch-first approach to acute aortic dissection, with anastomosis of the supra aortic vessels prior to commencing cardiopulmonary bypass. Methods Since 2012, 41 patients (aortic dissection, 36; arch aneurysm, 5) have undergone the modified procedure. Procedurally, the implanted graft was used as a landing zone for second-stage endovascular stent-graft deployment intended to manage the residual descending dissection. Antegrade and retrograde systemic perfusion was instituted during cardioplegic arrest. The brain was actively perfused via the graft throughout the procedure. Results Arch replacement surgery could generally be completed within approximately 4 h. During a 2-year period of aortic dissection or arch aneurysm treatment, only four anastomoses were required during the first stage of operation: two in the aorta, and one each in the innominate and left common carotid arteries. No patient died of surgical causes, and no stent grafts were deployed into the false lumen, a characteristic of procedures using traditionally antegrade deployment. Conclusion We recommend that our procedure for acute aortic dissection be performed in two stages (graft replacement first and stent graft deployment second), particularly for patients underwent preoperative hypotesion. If malperfusion syndrome still exists after graft replacement, stent graft should be deployed in one stage. The arch aneurysm can be treated in one stage because there is no concern about false lumen deployment.

The ahead geological prospecting of severely weathered surrounding rock in a tunnel is challenging due to complex geological conditions. Hence, the best approach is to use a variety of geophysical exploration methods. In this study, we have applied seismic, electrical resistivity (ER), and transient electromagnetic (TEM) methodologies for ahead prospecting of the highly weathered and complex surrounding rock at the diversion tunnel of the Hongyan River to Stone River Water Transfer Project in Shaanxi Province, China. The seismic method was employed to detect structural information for an area of 100 m from the front of the tunnel, the TEM method was used to obtain the resistivity information within 60 m, and the ER method was conducted to obtain detailed resistivity information over a range of 30 m. The integrated results generated a comprehensive interpretation of the geological body located within 100 m of the front of the tunnel. We divided this geological area into intact, severely weathered, and slightly weathered sections. Information on the water content of each section was also produced. The results of subsequent excavations are consistent with our results, proving the effectiveness and feasibility of a comprehensive approach for analyzing highly weathered and complex surrounding rock.

As a new atomically layered, two-dimensional material, tin (IV) diselenide (SnSe2) has attracted extensive attention due to its compelling application in electronics and optoelectronics. However, the great challenge of impurities and the preparation of high-quality ultrathin SnSe2 nanoflakes has hindered far-reaching research and SnSe2 practical applications so far. Therefore, a facile chemical vapor deposition (CVD) method is employed to synthesize large-scale ultrathin SnSe2 flakes on mica substrates using SnSe and Se powder as precursors. The structural characteristics and crystalline quality of the product were investigated. Moreover, Raman characterizations indicate that the intensity of A1g peak and Eg peak, and the Raman shift of Eg are associated with the thickness of the SnSe2 nanoflakes. The ultrathin SnSe2 nanoflakes show a strong surface-enhanced Raman spectroscopy (SERS) activity for Rhodamine 6G (R6G) molecules. Theoretical explanations for the enhancement principle based on the chemical enhancement mechanism and charge transfer diagram between R6G and SnSe2 are provided. The results demonstrate that the ultrathin SnSe2 flakes are high-quality single crystal and can be exploited for microanalysis detection and optoelectronic application.